#!/usr/bin/python
# -*- coding: UTF-8 -*-

import tensorflow as tf
# 科学计算模块
import numpy as np


x_data = np.random.rand(1000).astype(np.float32)
y_data = x_data * 0.1 + 0.3

## 创建训练模型开始
Weights = tf.Variable(tf.random_uniform([1],-1,1))
biases = tf.Variable(tf.zeros([1]))

y = x_data * Weights + biases

loss = tf.reduce_mean(tf.square(y - y_data))

optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(loss)

init = tf.initialize_all_variables()
## 创建训练模型结束

sess = tf.Session()
sess.run(init)

for step in range(2000):
    sess.run(train)
    if step % 20 == 0:
        print(step,sess.run(Weights),sess.run(biases))